Rolling bearing fault diagnosis based on the enhanced channel attention network
Author:
Affiliation:
1. Department of Automation, Zhejiang University of Technology, Hangzhou, China
2. Ningbo Zhongyi Automation Equipment Co LTD, Ningbo, China
Funder
National Key R&D Funding
The Zhejiang Provincial Natural Science Foundation of China for Distinguished Young Scholars
Publisher
Informa UK Limited
Subject
Computer Graphics and Computer-Aided Design,Computer Vision and Pattern Recognition,Computational Mechanics
Link
https://www.tandfonline.com/doi/pdf/10.1080/23335777.2022.2163705
Reference28 articles.
1. Fault Severity Classification and Size Estimation for Ball Bearings Based on Vibration Mechanism
2. Investigation on early fault classification for rolling element bearing based on the optimal frequency band determination
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